Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads

Abstract: Electrocardiographic (ECG) T-wave endpoint (Tend) identification suffers lack of reliability due to the presence of noise and variability among leads. Tend identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve Tend identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable Tend identification. To this aim Tend measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that Tend distributions have not statistically different median values (CHS: 340 ms vs. 340 ms, respectively; AMIP: 325 ms vs. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; P<10-27). Thus, measuring Tend from the 15-dependent-lead DTWs is statistically equivalent to measuring Tend from the 8-independent-lead DTWs. In conclusion, for the clinical purpose of automatic Tend identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the Tend determination from 15 dependent lead DTWs.